pathikrit

val n = 9
val s = Math.sqrt(n).toInt
type Board = IndexedSeq[IndexedSeq[Int]]
 
def solve(board: Board, cell: Int = 0): Option[Board] = (cell%n, cell/n) match {
  case (r, `n`) => Some(board)
  case (r, c) if board(r)(c) > 0 => solve(board, cell + 1)
  case (r, c) =>
    def guess(x: Int) = solve(board.updated(r, board(r).updated(c, x)), cell + 1)  
    val used = board.indices.flatMap(i => Seq(board(r)(i), board(i)(c), board(s*(r/s) + i/s)(s*(c/s) + i%s)))

vmarquez

  object Test {   
    import scalaz.{Lens,State}   
    case class BlahConfig(server: Int, l: List[Int]) 
     
    def doStuff(i: Int) = State[BlahConfig,Int]( c => (c.copy(l = i :: c.l), c.server) ) 
   
    case class FooConfig(val password: String) 
   
    def doSomeStuff(i: Int) = State[FooConfig, String](c =>(c, c.password)) 
    

obolton

AWS ELB with Node.js and WebSockets

This assumes that:

• You are using Nginx.
• You want to accept incoming connections on port 80.
• Your Node.js app is listening on port 3000.
• You want to be able to connect to your Node.js instance directly as well as via the load balancer.

####1. Create load balancer

johnynek

use std::comm::{Receiver, channel};
use std::io;
use std::mem::replace;
use std::task::spawn;

struct Future<'a, A> {
  state: FutureState<'a, A>
}

jdegoes

Introduction

LambdaConf has multiple tracks, so no attendee can possibly attend all sessions.

Yet, we'd like to schedule the sessions to maximize attendee happiness (for some definition of "maximum" and "happiness").

Sounds like a job for functional programming!

Your mission, should you choose to accept it, is to write a small functional program to produce an "optimal" schedule (your schedule may have any number of tracks you want -- you do not have to stick with 3 or 4).

t32k

foobar, foo, bar, baz, qux, quux, corge, grault, garply, waldo, fred, plugh, xyzzy, thud

• ASCII.jp：技術文書に頻出する「foobar」って何だ？｜今さら聞けないIT英語

johnynek

// Run this with scala <filename>

/**
 * A Two-phase commit Monad
 */
trait Transaction[+T] {
  def map[U](fn: T => U): Transaction[U] = flatMap { t => Constant(fn(t)) }
  def flatMap[U](fn: T => Transaction[U]): Transaction[U] =
    FlatMapped(this, fn)

vmadman

[program:lss]
process_name=Shipper
command=java -jar /usr/local/logstash/bin/logstash-1.1.9-monolithic.jar agent --config /usr/local/logstash/conf/shipper.conf --log /usr/local/logstash/log/shipper.log
user=logstash
startretries=3
redirect_stderr=true
std_out_logfile=NONE
startsecs=3
environment=HOME="/usr/local/logstash/"

viktorklang

/*
Copyright 2013 Viktor Klang
   Licensed under the Apache License, Version 2.0 (the "License");
   you may not use this file except in compliance with the License.
   You may obtain a copy of the License at
       http://www.apache.org/licenses/LICENSE-2.0
   Unless required by applicable law or agreed to in writing, software
   distributed under the License is distributed on an "AS IS" BASIS,
   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
   See the License for the specific language governing permissions and

vlfig

import scala.collection.mutable.WeakHashMap

/**
  * Utility traits for classes whose companion objects are to
  * intern their instances, never creating repeated objects.
  *
  * Instances are cached based on their immutable
  * arguments, as provided to companion object's {{apply()}}.
  */